Interactive scheduling as a constraint satisfiability problem

1990 ◽  
Vol 1 (1-4) ◽  
pp. 49-73 ◽  
Author(s):  
Ronen Feldman ◽  
Martin Charles Golumbic
Keyword(s):  
Satisfiability Problem ◽  
Constraint Satisfiability ◽  
Interactive Scheduling

scholarly journals Algorithms for Workflow Satisfiability Problem with User-independent Constraints

2020 ◽  
Vol 1 (1) ◽  
pp. 25-38
Author(s):  
Gregory Gutin
Keyword(s):  
Information Security ◽  
Access Control ◽  
Real World ◽  
Computational Experiments ◽  
Satisfiability Problem ◽  
Iterative Approach ◽  
Constraint Satisfiability ◽  
Fruitful Research

The Workflow Satisfiability Problem (WSP) is a problem of interest in access control of information security. In its simplest form, the problem coincides with the Constraint Satisfiability Problem, where the number of variables is usually much smaller than the number of values. Wang and Li (ACM Trans. Inf. Syst. Secur. 2010) were the first to study the WSP as a problem parameterized by the number of variables. Their paper initiated very fruitful research surveyed by Cohen, Crampton, Gutin and Wahlström (2017). In this paper, we overview more recent WSP algorithmic developments and discuss computational experiments performed on two new testbeds of WSP instances. These WSP instances are closer to real-world ones than those by Karapetyan et al. (JAIR 2019). One of the two testbeds is generated using a novel iterative approach for obtaining computationally hard WSP instances.

OMP-26 - An interactive scheduling tool for the 26 meter subnetwork

1993 ◽  
Author(s):  
Jody Rosas ◽  
Elmain Martinez ◽  
Lynne Cooper
Keyword(s):  
Scheduling Tool ◽  
Interactive Scheduling

A SERVICE FOR SOLVING BOOLEAN SATISFIABILITY PROBLEM USING NVIDIA CUDA TECHNOLOGY

2017 ◽  
Vol 4 (56) ◽  
pp. 107-114
Author(s):  
A. D. Kolosov ◽  
◽  
V. O. Gorovoy ◽  
V. V. Kondratiev ◽  
◽  
...  
Keyword(s):  
Boolean Satisfiability ◽  
Satisfiability Problem ◽  
Boolean Satisfiability Problem ◽  
Nvidia Cuda ◽  
Cuda Technology

scholarly journals Simplest randomK-satisfiability problem

2001 ◽  
Vol 63 (2) ◽  
Author(s):  
Federico Ricci-Tersenghi ◽  
Martin Weigt ◽  
Riccardo Zecchina
Keyword(s):  
Satisfiability Problem

Unsatisfiable Core Analysis and Aggregates for Optimum Stable Model Search

2020 ◽  
Vol 176 (3-4) ◽  
pp. 271-297
Author(s):  
Mario Alviano ◽  
Carmine Dodaro
Keyword(s):  
State Of The Art ◽  
Answer Set Programming ◽  
Efficient Algorithms ◽  
Satisfiability Problem ◽  
Core Analysis ◽  
Stable Model ◽  
Maximum Satisfiability ◽  
Model Search ◽  
Unsatisfiable Core ◽  
Stable Models

Many efficient algorithms for the computation of optimum stable models in the context of Answer Set Programming (ASP) are based on unsatisfiable core analysis. Among them, algorithm OLL was the first introduced in the context of ASP, whereas algorithms ONE and PMRES were first introduced for solving the Maximum Satisfiability problem (MaxSAT) and later on adapted to ASP. In this paper, we present the porting to ASP of another state-of-the-art algorithm introduced for MaxSAT, namely K, which generalizes ONE and PMRES. Moreover, we present a new algorithm called OLL-IN-ONE that compactly encodes all aggregates of OLL by taking advantage of shared aggregate sets propagators. The performance of the algorithms have been empirically compared on instances taken from the latest ASP Competition.

Algorithms for the maximum satisfiability problem

Computing ◽  
1990 ◽  
Vol 44 (4) ◽  
pp. 279-303 ◽  
Author(s):  
Pierre Hansen ◽  
Brigitte Jaumard
Keyword(s):  
Satisfiability Problem ◽  
Maximum Satisfiability

scholarly journals GASAT: A Genetic Local Search Algorithm for the Satisfiability Problem

2006 ◽  
Vol 14 (2) ◽  
pp. 223-253 ◽  
Author(s):  
Frédéric Lardeux ◽  
Frédéric Saubion ◽  
Jin-Kao Hao
Keyword(s):  
Tabu Search ◽  
Local Search ◽  
Hybrid Algorithm ◽  
State Of The Art ◽  
Search Algorithm ◽  
Satisfiability Problem ◽  
Local Search Algorithm ◽  
Overall Performance ◽  
Genetic Local Search ◽  
Search Stage

This paper presents GASAT, a hybrid algorithm for the satisfiability problem (SAT). The main feature of GASAT is that it includes a recombination stage based on a specific crossover and a tabu search stage. We have conducted experiments to evaluate the different components of GASAT and to compare its overall performance with state-of-the-art SAT algorithms. These experiments show that GASAT provides very competitive results.

DPLL-like satisfiability problem solver over the system of anf equations

2021 ◽  
pp. 187-190
Author(s):  
A.V. Tkachev ◽  
K. V. Kalgin
Keyword(s):  
Satisfiability Problem ◽  
Problem Solver

Boosting branch-and-bound MaxSAT solvers with clause learning

2021 ◽  
pp. 1-21
Author(s):  
Chu-Min Li ◽  
Zhenxing Xu ◽  
Jordi Coll ◽  
Felip Manyà ◽  
Djamal Habet ◽  
...  
Keyword(s):  
Experimental Investigation ◽  
Combinatorial Optimization ◽  
Problem Solving ◽  
Branch And Bound ◽  
Real World ◽  
Optimization Problems ◽  
Satisfiability Problem ◽  
Maximum Satisfiability ◽  
Combinatorial Optimization Problems ◽  
Clause Learning

The Maximum Satisfiability Problem, or MaxSAT, offers a suitable problem solving formalism for combinatorial optimization problems. Nevertheless, MaxSAT solvers implementing the Branch-and-Bound (BnB) scheme have not succeeded in solving challenging real-world optimization problems. It is widely believed that BnB MaxSAT solvers are only superior on random and some specific crafted instances. At the same time, SAT-based MaxSAT solvers perform particularly well on real-world instances. To overcome this shortcoming of BnB MaxSAT solvers, this paper proposes a new BnB MaxSAT solver called MaxCDCL. The main feature of MaxCDCL is the combination of clause learning of soft conflicts and an efficient bounding procedure. Moreover, the paper reports on an experimental investigation showing that MaxCDCL is competitive when compared with the best performing solvers of the 2020 MaxSAT Evaluation. MaxCDCL performs very well on real-world instances, and solves a number of instances that other solvers cannot solve. Furthermore, MaxCDCL, when combined with the best performing MaxSAT solvers, solves the highest number of instances of a collection from all the MaxSAT evaluations held so far.

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